How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
.svg" alt="Documentation Status">
The main features of amenra/guardbench are: Evaluation Benchmarks.
Projects with overlapping indexed features include: pyspur-dev/pyspur. datawhalechina/prompt-engineering-for-developers — This project is a technical curriculum and development guide focused on large language model prompt engineering,… ai45lab/openrt — Open-source red teaming framework for MLLMs with 42+ attack methods. ailab-cvc/seed-bench — (CVPR2024)A benchmark for evaluating Multimodal LLMs using multiple-choice questions. albertwy/gpt-4v-evaluation — Data for evaluating GPT-4V. aifeg/benchlmm — [ECCV 2024] BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models.
This project is a technical curriculum and development guide focused on large language model prompt engineering, fine-tuning, and the creation of retrieval augmented generation applications. It serves as a comprehensive resource for developers to master crafting precise instructions and textual patterns to improve the quality and predictability of model outputs. The material covers the end-to-end workflow of adapting open-source models to specific datasets and integrating language models with vector databases to generate responses based on private information. It also provides a systematic ap
Open-source red teaming framework for MLLMs with 42+ attack methods
ECCV 2024 BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models
